Daniel Kahneman, Olivier Sibony, and Cass R. Sunstein
PositiveLos Angeles Review of BooksIn Noise, academics Daniel Kahneman, Cass Sunstein, and Olivier Sibony synthesize a large existing literature on human and algorithmic decision-making to do exactly that: they provide crisp measurements and examples of error, breaking them down into noise and bias. While bias has dominated headlines, with allegations about racial biases in the criminal justice system—accentuated by our determination to acknowledge and adjust for centuries of racial discrimination—the authors show why noise is typically a much bigger problem ... The authors make a convincing case that pattern noise is pervasive in human judgment, and usually much higher—noisier—than level noise ... Noise also presents psychological reasons for why noise arises. This is useful for considering how we might lower or eliminate it ... This book isn’t just for professionals. It should also change the way individuals evaluate their everyday decision-making and interactions ... Noise will change how we think about human decision-making, and how we decide to accommodate machines. The stakes are large, and the book timely.
